Design is where DAS succeeds or struggles. This chapter teaches you to turn a broad ambition into a sharp, testable focus and a small set of actions people can actually do this week or month. You’ll learn to write action titles with verbs, add four concise guide sentences (plan, act, feel, reflect), and balance “easy wins” with light stretch. We cover tag design in depth: how to mix outcome tags (e.g., coordination, clarity), human tags (energy, psychological safety), and risk tags (overload, waiting), so analysis later has real signal. You’ll leave with reusable templates, and a pattern for scoping 5–7 actions over 6–8 weeks. Above all, you’ll see task design as a practical service to participants: lower the threshold, honor their time, and make it obvious why this helps their work today.
A DAS study always starts with the design step. What could participants be asked to do in order for new insights to be generated? Before this question can be answered, however, the study leader needs to articulate a focused research question (RQ). What is it they want to inquire around, and why should anyone even care? Without a good RQ that people care about, the risk is that participants’ time is wasted with pointless action tasks. A good RQ has one topic, one key problem, can be answered by collecting post-action reflections, is easily understood, and cannot be answered with yes/no.
The RQ in my own teaching has for more than a decade been the same: “How to make people more entrepreneurial?”. I design action tasks that I believe will make people more entrepreneurial, with headings such as: “Talk to 100 key people”, “Discuss price issues with a potential customer”, “Ask a person for something and get rejected”, or “Experience an emotional setback related to a key external person” (Lackéus, 2024). The heading must have a verb. Further, each designed action task must have a description that follows Kolb’s (1984) action-reflection cycle, outlining how participants should plan, act, feel and then reflect afterwards. For example:
Task heading: “Ask a person for something and get rejected“
Task description: “Experiment by asking an external person for something significant to your project (not just a meeting), and getting a clear no from this person, i.e. get rejected. Reflect here afterwards on how it felt, what you learned from it and how you will do next time around”.
Task heading: “Talk to 100 key people“
Task description: “Discuss with and communicate value to others by talking to 100 external persons, be it customers, experts, value chain people, network actors, etc. Reflect here afterwards on how it felt and what you learned from it.“
A set of action tasks is also accompanied by a set of 10-25 so-called “tags”, purposefully designed by the study leader. Each tag is a predefined impact indicator consisting of 1-4 words selectable by participants with a simple press of a digital button in the app. This acts as a quick quantification of effects and empowers the analysis afterwards. Some example tags I often use with my students include entrepreneurial competencies such as “better at initiative-taking”, “more motivated” and “increased creativity” (Lackéus, 2024). Students can then with a simple press of a button self-identify when they feel that they have developed any of these competencies. This is how I use DAS to quantitatively probe for effects related to my RQ.
Each year, I carefully analyse my students’ post-action reflections and taggings, and revise the design of task headings, task descriptions and tags for next year based on insights I get from reading and commenting upon my students’ reflections. The process increases my understanding of how people become more entrepreneurial. I can then write research articles about my insights and illustrate them with primary data from my students. If I collaborate with other teachers in a scientific community of practice, we can use the same sets of action tasks and tags and compare student reflections and taggings across organisations, thus increasing the rigor. If we are many teachers, we can also collect teacher reflections to complement the causal pattern analysis.
4.1 What is an action task?
An action task is fundamentally a hypothesis around what might help another person, either to learn something or to succeed with some other goal. An action task can thus be seen as a social experiment, an idea for a cause aimed to trigger an effect of some kind, or an attempt to answer the question “what works?” in a given context. It is thus a tool to go from theory to practice, from generic idea to contextual action, and back. A good action task gives participants support throughout the entire action-reflection cycle, triggers positive or negative emotions, and results in interesting reflections from participants related to the RQ. A good action task contributes to a good balance between work (creating value for others) and learning (growing as a person). Read more about such work-learn balance in Lackéus (2023).
4.2 Example action tasks
After 15 years of DAS usage around the world, there are numerous examples. The ones given here are included due to the availability of detailed published descriptions. Economics students on university level have been asked to take an initiative for positive change in their life and to give developmental feedback to someone at home (Westerberg, 2022). Entrepreneurship students have been asked to contact external stakeholders and to reflect whenever something emotional happened to them (Larsen and Neergaard, 2024). Other entrepreneurship students have been asked to reflect after course sessions and activities in a multi-assessment approach combining DAS and surveys (Hmama and Rih, 2025). Vocational school students on work placements have been asked to paint a customer’s house on the outside (Lackéus and Sävetun, 2021) and to manage a retail store (Lackéus and Sävetun, 2025). Primary school students have been asked to reflect upon speaking English with an AI-based conversational agent (Ericsson and Johansson, 2023).
Turning to employee learning, primary school teachers have been asked to work with various language development activities such as reading aloud, discussing difficult words in class and using images to explain words (Brandt and Viebke, 2023). Coffee shop owners have been asked to adopt new circular composting practices (Morland and Lever, 2024). Social workers have been asked to implement a new method for cross-unit collaboration (Tjulin and Klockmo, 2023). Transformational change leaders in healthcare have been asked to challenge established norms, create meeting forums for mutual reflection and to address organisational gaps they identify (Boström et al., 2025). Many more examples can be found in the Loopme library at library.loopme.io.
4.3 Common challenges in the design phase
DAS triggers strong feelings among newcomers receiving method training (Lackéus, 2025). While they see opportunities to improve their teaching through a stronger student focus, to work in a more data-driven way and to become part of a scientific community, they also struggle with confusion, stress and worry. Common struggles in the design phase are finding time to learn a new method, grasping the inherent complexity of DAS for study leaders, formulating a focused RQ and designing good action tasks and tags. Many find the DAS handbook to be useful here (Lackéus, 2021).
4.4 The end result of the design phase
The outcome of the design phase is a plan consisting of a focused RQ, a good answer to the So what? question, a set of 5-15 action tasks to be given to a well-defined group of 15-100 participants and a set of 10-25 impact tags suitable for the specific context. We ask DAS training participants to summarize their study plan in a one-page canvas template in Powerpoint or similar.